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ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

The technology will offer supportless DIW of complex structures using vinyl ester resin, facilitated by multidirectional 6 axis printing.

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

The technologies provide additively manufactured thermal protection system.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

Reflective and emissive surfaces are designed with heat retention as opposed to the current state of the art oven and furnaces which use non-reflective surfaces. Heat is absorbed and transferred to the exterior of the heated appliances.

This invention focuses on improving the ceramic yield of preceramic polymers by tuning the crosslinking process that occurs during vat photopolymerization (VP).

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

Using all polymer formulations, the PIP densification is improved almost 70% over traditional preceramic polymers and PIP material leading to cost and times saving for densifying ceramic composites made from powder or fibers.